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Wolfgang Förstner

    9 mai 1946
    Die Suche nach groben Fehlern in photogrammetrischen Lageblöcken
    Statistische Verfahren für die automatische Bildanalyse und ihre Bewertung bei der Objekterkennung und -vermessung
    Robust computer vision
    Semantic modeling for the acquisition of topographic information from images and maps
    Photogrammetric Computer Vision
    • Photogrammetric Computer Vision

      Statistics, Geometry, Orientation and Reconstruction

      • 816pages
      • 29 heures de lecture
      4,0(1)Évaluer

      This textbook presents a statistical perspective on the geometry of multiple view analysis, essential for camera calibration, orientation, and geometric scene reconstruction using image features. Authored by experts in geodesy and computer vision, it uniquely merges photogrammetry and computer vision. The first part introduces estimation theory, focusing on Bayesian estimation, variance components, and sequential estimation, emphasizing the importance of statistically sound diagnostics in vision metrology. The second part explores 2D and 3D geometric reasoning through projective geometry, including oriented projective geometry and statistically optimal estimation tools for geometric entities and transformations, relevant for uncertain reasoning in point clouds. The third part focuses on modeling the geometry of single and multiple cameras, covering calibration, orientation, and the statistical evaluation of corresponding scene features based on geometric image features. The authors provide algorithms for various geometric computation challenges in vision metrology, supported by mathematical justifications and statistical analyses for thorough evaluations. Each chapter is self-contained, featuring numerous figures and exercises, along with an appendix detailing basic mathematical notation and a comprehensive index. This resource is suitable for undergraduate and graduate courses in photogrammetry, computer vision, and computer

      Photogrammetric Computer Vision
    • Acquiring spatial data for geoinformation systems is still mainly done by human operators who analyze images using classical photogrammetric equipment or digitize maps, possibly assisted by some low level image processing. Automation of these tasks is difficult due to the complexity of the object, the topography, and the deficiency of current pattern recognition and image analysis tools for achieving a reliable transition from the data to the high level description of topographic objects. It appears that progress in automation only can be achieved by incorporating domain-specific semantic models into the analysis procedures. This volume collects papers which were presented at the Workshop "SMATI '97„. The workshop focused on “Semantic Modeling for the Acquisition of Topographic Information from Images and Maps." This volume offers a comprehensive selection of high-quality and in-depth contributions by experts of the field coming from leading research institutes, treating both theoretical and implementation issues and integrating aspects of photogrammetry, cartography, computer vision, and image understanding.

      Semantic modeling for the acquisition of topographic information from images and maps